Viralyze

Viralyze simulates a real-world data analyst role at a social media analytics firm. Using 5,000 synthetic posts across platforms and regions, it extracts cross-platform insights, builds views, and prepares dashboard-ready queries using SQL Server (T-SQL).

Provide actionable answers to marketing and content teams about platform performance, hashtag virality, content effectiveness, and monthly engagement trends — all via optimized SQL logic.

• SQL Server (T-SQL): Advanced querying & modular views
• Window Functions: ROW_NUMBER, DENSE_RANK, LAG
• Custom View: Enhanced_Social_Media_Trends
• Tableau: Dashboard-ready metrics & trend visuals
• Git & GitHub: Version control & publishing
• VS Code + SSMS: Development environment

• Executed full workflow: schema mapping, insight derivation, and dashboard prep
• Wrote modular SQL using CTEs and reusable views
• Simulated time-series logic via ROW_NUMBER() in absence of timestamps
• Created engagement KPIs, hashtag analytics, and virality detection metrics
• Engineered a robust Enhanced_Social_Media_Trends view for stakeholder-ready outputs

• 📊 Instagram had the highest engagement rate (0.82), followed by TikTok (0.64)
• 💥 Detected a viral TikTok post with 281.74 ER — over 440× average
• 📅 September had the strongest momentum across platforms (2.5× TikTok)
• 📌 Europe had the most consistent hashtag usage — strong brand retention
• + Additional insights on regional breakdowns, top content types, and hashtag spikes included in the dashboard